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	Author	Oscar Argudo; Marc Comino; Antonio Chica; Carlos Andujar; Felipe Lumbreras
	Title	Segmentation of aerial images for plausible detail synthesis			Type	Journal Article
	Year	2018	Publication	Computers & Graphics	Abbreviated Journal	CG
	Volume	71	Issue		Pages	23-34
	Keywords	Terrain editing; Detail synthesis; Vegetation synthesis; Terrain rendering; Image segmentation
	Abstract	The visual enrichment of digital terrain models with plausible synthetic detail requires the segmentation of aerial images into a suitable collection of categories. In this paper we present a complete pipeline for segmenting high-resolution aerial images into a user-defined set of categories distinguishing e.g. terrain, sand, snow, water, and different types of vegetation. This segmentation-for-synthesis problem implies that per-pixel categories must be established according to the algorithms chosen for rendering the synthetic detail. This precludes the definition of a universal set of labels and hinders the construction of large training sets. Since artists might choose to add new categories on the fly, the whole pipeline must be robust against unbalanced datasets, and fast on both training and inference. Under these constraints, we analyze the contribution of common per-pixel descriptors, and compare the performance of state-of-the-art supervised learning algorithms. We report the findings of two user studies. The first one was conducted to analyze human accuracy when manually labeling aerial images. The second user study compares detailed terrains built using different segmentation strategies, including official land cover maps. These studies demonstrate that our approach can be used to turn digital elevation models into fully-featured, detailed terrains with minimal authoring efforts.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0097-8493	ISBN		Medium
	Area		Expedition		Conference
	Notes	MSIAU; 600.086; 600.118			Approved	no
	Call Number	Admin @ si @ ACC2018			Serial	3147
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	Author	Ruth Aylett; Ginevra Castellano; Bogdan Raducanu; Ana Paiva; Marc Hanheide
	Title	Long-term socially perceptive and interactive robot companions: challenges and future perspectives			Type	Conference Article
	Year	2011	Publication	13th International Conference on Multimodal Interaction	Abbreviated Journal
	Volume		Issue		Pages	323-326
	Keywords	human-robot interaction, multimodal interaction, social robotics
	Abstract	This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours.
	Address	Alicante
	Corporate Author				Thesis
	Publisher	ACM	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4503-0641-6	Medium
	Area		Expedition		Conference	ICMI
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ ACR2011			Serial	1888
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	Author	Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi
	Title	Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	133-140
	Keywords
	Abstract	In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model.
	Address	Madeira; Portugal; June 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG; 605.203			Approved	no
	Call Number	Admin @ si @ ACS2013			Serial	2328
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	Author	Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi
	Title	Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars			Type	Journal Article
	Year	2015	Publication	Neurocomputing	Abbreviated Journal	NEUCOM
	Volume	150	Issue	A	Pages	147-154
	Keywords	document image analysis; stochastic context-free grammars; text classication features
	Abstract	In this paper we dene a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents. Two sets of text classication features are used to perform an initial classication of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models and the results showed that the proposed grammatical model outperformed the other methods. Furthermore, grammars also provide the document structure along with its segmentation.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 601.158; 600.077; 600.061			Approved	no
	Call Number	Admin @ si @ ACS2015			Serial	2531
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	Author	Maedeh Aghaei; Mariella Dimiccoli; C. Canton-Ferrer; Petia Radeva
	Title	Towards social pattern characterization from egocentric photo-streams			Type	Journal Article
	Year	2018	Publication	Computer Vision and Image Understanding	Abbreviated Journal	CVIU
	Volume	171	Issue		Pages	104-117
	Keywords	Social pattern characterization; Social signal extraction; Lifelogging; Convolutional and recurrent neural networks
	Abstract	Following the increasingly popular trend of social interaction analysis in egocentric vision, this article presents a comprehensive pipeline for automatic social pattern characterization of a wearable photo-camera user. The proposed framework relies merely on the visual analysis of egocentric photo-streams and consists of three major steps. The first step is to detect social interactions of the user where the impact of several social signals on the task is explored. The detected social events are inspected in the second step for categorization into different social meetings. These two steps act at event-level where each potential social event is modeled as a multi-dimensional time-series, whose dimensions correspond to a set of relevant features for each task; finally, LSTM is employed to classify the time-series. The last step of the framework is to characterize social patterns of the user. Our goal is to quantify the duration, the diversity and the frequency of the user social relations in various social situations. This goal is achieved by the discovery of recurrences of the same people across the whole set of social events related to the user. Experimental evaluation over EgoSocialStyle – the proposed dataset in this work, and EGO-GROUP demonstrates promising results on the task of social pattern characterization from egocentric photo-streams.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB; no proj			Approved	no
	Call Number	Admin @ si @ ADC2018			Serial	3022
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	Author	Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva
	Title	Towards social interaction detection in egocentric photo-streams			Type	Conference Article
	Year	2015	Publication	Proceedings of SPIE, 8th International Conference on Machine Vision , ICMV 2015	Abbreviated Journal
	Volume	9875	Issue		Pages
	Keywords
	Abstract	Detecting social interaction in videos relying solely on visual cues is a valuable task that is receiving increasing attention in recent years. In this work, we address this problem in the challenging domain of egocentric photo-streams captured by a low temporal resolution wearable camera (2fpm). The major difficulties to be handled in this context are the sparsity of observations as well as unpredictability of camera motion and attention orientation due to the fact that the camera is worn as part of clothing. Our method consists of four steps: multi-faces localization and tracking, 3D localization, pose estimation and analysis of f-formations. By estimating pair-to-pair interaction probabilities over the sequence, our method states the presence or absence of interaction with the camera wearer and specifies which people are more involved in the interaction. We tested our method over a dataset of 18.000 images and we show its reliability on our considered purpose. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICMV
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ ADR2015a			Serial	2702
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	Author	Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva
	Title	Multi-Face Tracking by Extended Bag-of-Tracklets in Egocentric Videos			Type	Miscellaneous
	Year	2015	Publication	Arxiv	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Egocentric images offer a hands-free way to record daily experiences and special events, where social interactions are of special interest. A natural question that arises is how to extract and track the appearance of multiple persons in a social event captured by a wearable camera. In this paper, we propose a novel method to find correspondences of multiple-faces in low temporal resolution egocentric sequences acquired through a wearable camera. This kind of sequences imposes additional challenges to the multitracking problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution (2 fpm), abrupt changes in the field of view, in illumination conditions and in the target location are very frequent. To overcome such a difficulty, we propose to generate, for each detected face, a set of correspondences along the whole sequence that we call tracklet and to take advantage of their redundancy to deal with both false positive face detections and unreliable tracklets. Similar tracklets are grouped into the so called extended bag-of-tracklets (eBoT), which are aimed to correspond to specific persons. Finally, a prototype tracklet is extracted for each eBoT. We validated our method over a dataset of 18.000 images from 38 egocentric sequences with 52 trackable persons and compared to the state-of-the-art methods, demonstrating its effectiveness and robustness.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ ADR2015b			Serial	2713
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	Author	Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva
	Title	Multi-face tracking by extended bag-of-tracklets in egocentric photo-streams			Type	Journal Article
	Year	2016	Publication	Computer Vision and Image Understanding	Abbreviated Journal	CVIU
	Volume	149	Issue		Pages	146-156
	Keywords
	Abstract	Wearable cameras offer a hands-free way to record egocentric images of daily experiences, where social events are of special interest. The first step towards detection of social events is to track the appearance of multiple persons involved in them. In this paper, we propose a novel method to find correspondences of multiple faces in low temporal resolution egocentric videos acquired through a wearable camera. This kind of photo-stream imposes additional challenges to the multi-tracking problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution, abrupt changes in the field of view, in illumination condition and in the target location are highly frequent. To overcome such difficulties, we propose a multi-face tracking method that generates a set of tracklets through finding correspondences along the whole sequence for each detected face and takes advantage of the tracklets redundancy to deal with unreliable ones. Similar tracklets are grouped into the so called extended bag-of-tracklets (eBoT), which is aimed to correspond to a specific person. Finally, a prototype tracklet is extracted for each eBoT, where the occurred occlusions are estimated by relying on a new measure of confidence. We validated our approach over an extensive dataset of egocentric photo-streams and compared it to state of the art methods, demonstrating its effectiveness and robustness.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;			Approved	no
	Call Number	Admin @ si @ ADR2016b			Serial	2742
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	Author	Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva
	Title	With Whom Do I Interact? Detecting Social Interactions in Egocentric Photo-streams			Type	Conference Article
	Year	2016	Publication	23rd International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Given a user wearing a low frame rate wearable camera during a day, this work aims to automatically detect the moments when the user gets engaged into a social interaction solely by reviewing the automatically captured photos by the worn camera. The proposed method, inspired by the sociological concept of F-formation, exploits distance and orientation of the appearing individuals -with respect to the user- in the scene from a bird-view perspective. As a result, the interaction pattern over the sequence can be understood as a two-dimensional time series that corresponds to the temporal evolution of the distance and orientation features over time. A Long-Short Term Memory-based Recurrent Neural Network is then trained to classify each time series. Experimental evaluation over a dataset of 30.000 images has shown promising results on the proposed method for social interaction detection in egocentric photo-streams.
	Address	Cancun; Mexico; December 2016
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICPR
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ ADR2016d			Serial	2835
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	Author	Egils Avots; M. Daneshmanda; Andres Traumann; Sergio Escalera; G. Anbarjafaria
	Title	Automatic garment retexturing based on infrared information			Type	Journal Article
	Year	2016	Publication	Computers & Graphics	Abbreviated Journal	CG
	Volume	59	Issue		Pages	28-38
	Keywords	Garment Retexturing; Texture Mapping; Infrared Images; RGB-D Acquisition Devices; Shading
	Abstract	This paper introduces a new automatic technique for garment retexturing using a single static image along with the depth and infrared information obtained using the Microsoft Kinect II as the RGB-D acquisition device. First, the garment is segmented out from the image using either the Breadth-First Search algorithm or the semi-automatic procedure provided by the GrabCut method. Then texture domain coordinates are computed for each pixel belonging to the garment using normalised 3D information. Afterwards, shading is applied to the new colours from the texture image. As the main contribution of the proposed method, the latter information is obtained based on extracting a linear map transforming the colour present on the infrared image to that of the RGB colour channels. One of the most important impacts of this strategy is that the resulting retexturing algorithm is colour-, pattern- and lighting-invariant. The experimental results show that it can be used to produce realistic representations, which is substantiated through implementing it under various experimentation scenarios, involving varying lighting intensities and directions. Successful results are accomplished also on video sequences, as well as on images of subjects taking different poses. Based on the Mean Opinion Score analysis conducted on many randomly chosen users, it has been shown to produce more realistic-looking results compared to the existing state-of-the-art methods suggested in the literature. From a wide perspective, the proposed method can be used for retexturing all sorts of segmented surfaces, although the focus of this study is on garment retexturing, and the investigation of the configurations is steered accordingly, since the experiments target an application in the context of virtual fitting rooms.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	HuPBA;MILAB;			Approved	no
	Call Number	Admin @ si @ ADT2016			Serial	2759
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	Author	Sergio Alloza; Flavio Escribano; Sergi Delgado; Ciprian Corneanu; Sergio Escalera
	Title	XBadges. Identifying and training soft skills with commercial video games Improving persistence, risk taking & spatial reasoning with commercial video games and facial and emotional recognition system			Type	Conference Article
	Year	2017	Publication	4th Congreso de la Sociedad Española para las Ciencias del Videojuego	Abbreviated Journal
	Volume	1957	Issue		Pages	13-28
	Keywords	Video Games; Soft Skills; Training; Skilling Development; Emotions; Cognitive Abilities; Flappy Bird; Pacman; Tetris
	Abstract	XBadges is a research project based on the hypothesis that commercial video games (nonserious games) can train soft skills. We measure persistence, patial reasoning and risk taking before and after subjects paticipate in controlled game playing sessions. In addition, we have developed an automatic facial expression recognition system capable of inferring their emotions while playing, allowing us to study the role of emotions in soft skills acquisition. We have used Flappy Bird, Pacman and Tetris for assessing changes in persistence, risk taking and spatial reasoning respectively. Results show how playing Tetris significantly improves spatial reasoning and how playing Pacman significantly improves prudence in certain areas of behavior. As for emotions, they reveal that being concentrated helps to improve performance and skills acquisition. Frustration is also shown as a key element. With the results obtained we are able to glimpse multiple applications in areas which need soft skills development.
	Address	Barcelona; June 2017
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	COSECIVI; CEUR-WS
	Notes	HUPBA; no menciona			Approved	no
	Call Number	Admin @ si @ AED2017			Serial	3065
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	Author	Oscar Amoros; Sergio Escalera; Anna Puig
	Title	Adaboost GPU-based Classifier for Direct Volume Rendering			Type	Conference Article
	Year	2011	Publication	International Conference on Computer Graphics Theory and Applications	Abbreviated Journal
	Volume		Issue		Pages	215-219
	Keywords
	Abstract	In volume visualization, the voxel visibitity and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges.
	Address	Algarve, Portugal
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	GRAPP
	Notes	MILAB; HuPBA			Approved	no
	Call Number	Admin @ si @ AEP2011			Serial	1774
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	Author	Jon Almazan; Alicia Fornes; Ernest Valveny
	Title	A Non-Rigid Feature Extraction Method for Shape Recognition			Type	Conference Article
	Year	2011	Publication	11th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	987-991
	Keywords
	Abstract	This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost.
	Address	Beijing; China; September 2011
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-7695-4520-2	Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ AFV2011			Serial	1763
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	Author	Jon Almazan; Alicia Fornes; Ernest Valveny
	Title	A Deformable HOG-based Shape Descriptor			Type	Conference Article
	Year	2013	Publication	12th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	1022-1026
	Keywords
	Abstract	In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the computation of histograms of oriented gradients-based features over these points. Our results significantly outperform other descriptors in the literature for the task of hand-drawn shape recognition and handwritten word retrieval
	Address	Washington; USA; August 2013
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1520-5363	ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ AFV2013			Serial	2326
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	Author	Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca
	Title	Beyond the Static Camera: Issues and Trends in Active Vision			Type	Book Chapter
	Year	2011	Publication	Visual Analysis of Humans: Looking at People	Abbreviated Journal
	Volume		Issue	2	Pages	11-30
	Keywords
	Abstract	Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems.
	Address
	Corporate Author				Thesis
	Publisher	Springer London	Place of Publication		Editor	Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-85729-996-3	Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ AFX2011			Serial	1814
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